/* O(1) - no loops O(log N) - usually searching algorithms have log(n) if they are sorted (Binary Search) (not on hash maps though) O(n) - for loops while loops O(n*log(n)) - Sorting operations usually O(n^2) - Every element in a collection needs to be compared to ever other element. Two nested loops O(2^N) - O(n!) - you are adding a loop for every element. Iterating through half a collection is still O(n) Two separate collections: O(a + b) */ // Cheat Sheet: // What can cause time in a function? // Operations // Comparisons // Looping // Function call // Rule 1: Always worst Case // Rule 2: Remove Constants // + for steps in order // * for nested steps // Rule 3: Different inputs should have different variables. O(a+b). A and B arrays nested would be O(a*b) // Rule 4: Drop Non-dominant terms